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HESKO, B. et al.
Originální název
Simultaneous lesions and optic disc segmentation from ophthalmoscopic images
Anglický název
Druh
Stať ve sborníku v databázi WoS či Scopus
Originální abstrakt
In this paper we present a novel approach to retina images segmentation. Simultaneously, 5 classes of objects are segmented including microaneurysms, haemorrhages, hard and soft exudates and optic disc. Segmentation of these eye disease symptoms is not straightforward, segmented objects are small, granular and may not be present in all images. We employ deep learning with fully convolutional methods. For a comparison, two different convolutional networks are used, SegNet and PSPNet. They are based on deep classifiers; therefore, we were able to use pretrained weights and only fine-tune both networks. Results suggest, we have chosen a perspective approach because we reached promising results.
Anglický abstrakt
Klíčová slova
deep learning, ophthalmology, retina images, segmentation
Klíčová slova v angličtině
Autoři
Rok RIV
2019
Vydáno
05.10.2018
Nakladatel
Katedra biomedicínskeho inžinierstva a merania
Místo
Kočice
ISBN
978-80-8086-271-8
Kniha
YBERC 2018 International Conference Proceedings
Strany od
1
Strany do
6
Strany počet
BibTex
@inproceedings{BUT150379, author="Branislav {Hesko} and Vratislav {Harabiš}", title="Simultaneous lesions and optic disc segmentation from ophthalmoscopic images", booktitle="YBERC 2018 International Conference Proceedings", year="2018", pages="1--6", publisher="Katedra biomedicínskeho inžinierstva a merania", address="Kočice", isbn="978-80-8086-271-8" }